Vegetation is a significant source of outages for many utilities. In some regions from one quarter to one-half of all outages can be ascribed to vegetation. Vegetation encroachment initiated the massive North American northeastern outage of 2003. It is so critical for utility operations that utilities may have a vice president responsible for vegetation management. It can be costly for utilities to identify areas of high-risk vegetation encroachment. Scheduling and routing crews to prune the trees that require attention is often sub-optimal adding to the cost of vegetation management. Optimizing these processes can produce significant benefits in the form of fewer outages and reduced costs. I blogged previously about Energisa in Brazil who used satellite stereo imagery to prioritize and optimize tree pruning. At Distributech 2019 in New Orleans, Sainab Ninalowo and Dan Marron from ComEd described a pilot project in Chicago to use LiDAR imagery to not only prioritize and optimize but also to change the pricing structure for distribution tree trimming.
Currently, ComEd trims 25% of their service area every year so that their entire service area is covered every four years. In addition they perform reactive trimming – when they have a vegetation-related problem reported they dispatch a crew to resolve the problem. Statistics show that the number of vegetation-related outages (vegetation SAIDI) has been declining year over year. The contractors who do this work are currently paid by the circuit mile independent of tree density, so that a contractor working in a rural or suburban area with many trees is paid the same per mile as a contractor in an urban area with few trees.
ComEd has had experience using LiDAR for vegetation management for its transmission lines and decided on conducting a pilot project to apply the technology to its distribution network. It chose circuits in four areas in its service territory with a range of tree densities ranging from rural to urban. ComEd put the capture of LiDAR data and post-processing of the point clouds out to competitive bid and selected two vendors. For the LiDAR imagery acquisition fixed wing aircraft were used. Post-processing involved combining the distribution network from their GIS with the vegetation identified in the point cloud imagery and modeling cylinders around the cables to reflect the tolerances for vegetation encroachment (grow-ins and fall-ins).
Using the volume of vegetation encroachment in the cylinders it was possible to calculate the volume of tree trimming required. This made it possible to procure tree trimming services with a different pricing model, based on per cubic foot instead of per circuit mile. This change in procurement modus enables contractors to more accurately estimate labor and equipment costs and ComEd to prioritize their tree trimming based on the needs revealed by the data.
In addition to LiDAR cameras the aircraft were equipped with IR and hyperspectral sensors. The IR imagery made it possible to successfully identify weakened and unhealthy trees. The hyperspectral data was used to try to identify different tree species, but the results were not able to this reliably enough to recommend using this technology operationally.
The pilot has been deemed to be a success, although there are not yet direct cost comparison figures publicly available. In addition to the perceived benefits for vegetation management, ComEd has identified other significant benefits which can be derived from the LiDAR data. Based on the results of the pilot it is being recommended that LiDAR be phased in gradually for the entire network with the goal of conducting a LiDAR scan of the entire distribution network annually.
This is another example of how geospatial technology is fundamentally changing the utility industry, in this case how vegetation management services are procured.